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Record W1971384049 · doi:10.1586/egh.13.11

Evaluation of the small bowel in inflammatory bowel disease

2013· review· en· W1971384049 on OpenAlexaff
Garret Cullen, Fergal Donnellan, Glen Doherty, Martin P. Smith, Adam S. Cheifetz

Bibliographic record

VenueExpert Review of Gastroenterology & Hepatology · 2013
Typereview
Languageen
FieldMedicine
TopicGastrointestinal Bleeding Diagnosis and Treatment
Canadian institutionsVancouver General Hospital
Fundersnot available
KeywordsMedicineEnteroscopyCapsule endoscopyInflammatory bowel diseaseMagnetic resonance imagingRadiologyCrohn's diseaseColonoscopyUlcerative colitisEndoscopyGastroenterologyDiseaseInternal medicineColorectal cancer

Abstract

fetched live from OpenAlex

Crohn's disease is a chronic inflammatory bowel disease (IBD) that can affect the entire GI tract, and adequate visualization of the small bowel is imperative for both diagnosis and management. Magnetic resonance and computed tomography enterography have gradually replaced barium-based studies. Magnetic resonance enterography has the distinct advantage of avoiding ionizing radiation to which many patients with IBD are overexposed. Endoscopy-based techniques, including capsule endoscopy and device-assisted enteroscopy, allow direct visualization of the small bowel mucosa. Deep enteroscopy has the additional benefit of allowing sampling of the mucosa for histological analysis. Small intestine contrast ultrasound is rapidly gaining credence as an excellent, radiation-free imaging technique, but is not available in all countries. Other imaging modalities, such as positron emission tomography and leucocyte scintigraphy, continue to be studied and may have a role in specific circumstances. This review summarizes the evidence for the various techniques for evaluating the small bowel in IBD.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.414
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.059
GPT teacher head0.359
Teacher spread0.299 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designSystematic review
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations7
Published2013
Admission routes1
Has abstractyes

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